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Conditioning Information and Variance Bounds on Pricing Kernels with Higher-Order Moments: Theory and Evidence

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  • Fousseni Chabi-Yo
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    Abstract

    The author develops a strategy for utilizing higher moments and conditioning information efficiently, and hence improves on the variance bounds computed by Hansen and Jagannathan (1991, the HJ bound) and Gallant, Hansen, and Tauchen (1990, the GHT bound). The author's bound incorporates variance risk premia. It reaches the GHT bound when non-linearities in returns are not priced. The author also provides an optimally scaled bound with conditioning information, higher moments, and variance risk premia that improves on the Bekaert and Liu (2004, the BL bound) optimally scaled bound. This bound reaches the BL bound when nonlinearities in returns are not priced. When the conditional first four moments are misspecified, the author's optimally scaled bound remains a lower bound to the variance on pricing kernels, whereas the BL bound does not. The author empirically illustrates the behaviour of the bounds using Bekaert and Liu's (2004) econometric models. He also uses higher moments and conditioning information to provide distance measures that improve on the Hansen and Jagannathan distance measures. The author uses these distance measures to evaluate the performance of asset-pricing models. Some existing pricing kernels are able to describe returns ignoring the impact of higher moments and variance risk premia. When accounting for the impact of higher moments and variance risk premia, these same pricing kernels have difficulty in explaining returns on the assets and are unable to price non-linearities or higher moments.

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    Bibliographic Info

    Paper provided by Bank of Canada in its series Working Papers with number 06-38.

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    Length: 56 pages
    Date of creation: 2006
    Date of revision:
    Handle: RePEc:bca:bocawp:06-38

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    Keywords: Financial markets; Market structure and pricing;

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    1. Tobias J. Moskowitz & Mark Grinblatt, 1999. "Do Industries Explain Momentum?," Journal of Finance, American Finance Association, vol. 54(4), pages 1249-1290, 08.
    2. Wayne E. Ferson, 2001. "The Efficient Use of Conditioning Information in Portfolios," Journal of Finance, American Finance Association, vol. 56(3), pages 967-982, 06.
    3. Jagannathan, Ravi & Wang, Zhenyu, 1996. " The Conditional CAPM and the Cross-Section of Expected Returns," Journal of Finance, American Finance Association, vol. 51(1), pages 3-53, March.
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    12. Campbell, John & Cochrane, John, 2000. "Explaining the Poor Performance of Consumption-Based Asset Pricing Models," Scholarly Articles 3163265, Harvard University Department of Economics.
    13. Geert Bekaert & Jun Liu, 1999. "Conditioning Information and Variance Bounds on Pricing Kernels," NBER Working Papers 6880, National Bureau of Economic Research, Inc.
    14. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, 06.
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    16. Bakshi, Gurdip & Madan, Dilip, 2000. "Spanning and derivative-security valuation," Journal of Financial Economics, Elsevier, vol. 55(2), pages 205-238, February.
    17. John Y. Campbell, 2002. "Consumption-Based Asset Pricing," Harvard Institute of Economic Research Working Papers 1974, Harvard - Institute of Economic Research.
    18. Snow, Karl N, 1991. " Diagnosing Asset Pricing Models Using the Distribution of Asset Returns," Journal of Finance, American Finance Association, vol. 46(3), pages 955-83, July.
    19. Gallant, A. Ronald & Hansen, Lars Peter & Tauchen, George, 1990. "Using conditional moments of asset payoffs to infer the volatility of intertemporal marginal rates of substitution," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 141-179.
    20. Constantinides,George & Duffie,Darrel, 1992. "Asset pricing with heterogeneous consumers," Discussion Paper Serie A 381, University of Bonn, Germany.
    21. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
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